Medical Image Computing and Computer Assisted Intervention MICCAI 2021

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: image segmentation

Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning

Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty

Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality

Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction

Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular

Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging others; and clinical applications - oncology

Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound

*The conference was held virtually.

Inhalt
Image Registration.- Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement.- Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks.- Learning Unsupervised Parameter-specific Affine Transformation for Medical Images Registration.- Conditional Deformable Image Registration with Convolutional Neural Network.- A Deep Discontinuity-Preserving Image Registration Network.- End-to-end Ultrasound Frame to Volume Registration.- Cross-modal Attention for MRI and Ultrasound Volume Registration.- Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization.- SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings.- Weakly Supervised Registration of Prostate MRI and Histopathology Images.- 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer.- Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling.- Learning Dual Transformer Network for Diffeomorphic Registration.- Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases based on Deep Learning.- Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration.- Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence.- A Deep Network for Joint Registration and Parcellation of Cortical Surfaces.- 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT.- Equivariant Filters for Efficient Tracking in 3D Imaging.- Revisiting iterative highly efficient optimisation schemes in medical image registration.- Multi-scale Neural ODEs for 3D Medical Image Registration.- Image-Guided Interventions and Surgery.- Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images.- Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy.- Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks.- Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image.- Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation.- Real-Time Rotated Convolutional Descriptor for Surgical Environments.- Surgical Instruction Generation with Transformers.- Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation.- 2.5D Thermometry Maps for MRI-guided Tumor Ablation.- Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision.- EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos.- Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video.- C-arm positioning for spinal standard projections in different intra-operative settings.- Quantitative Assessments for Ultrasound Probe Calibration.- Intra-operative Update of Boundary Conditions for Patient-specific Surgical Simulation.- Deep Iterative 2D/3D Registration.- hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries.- Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data.- Surgical Data Science.- E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception.- CataNet: Predicting remaining cataract surgery duration.- Task Fingerprinting for Meta Learning in Biomedical Image Analysis.- Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants.- Surgical Planning and Simulation.- Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning.- A self-supervised deep framework for reference bony shape estimation in orthognathic surgical planning.-DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models.- Personalized CT Organ Dose Estimation from Scout Images.- High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs.- Effective semantic segmentation in Cataract surgery: What matters most?.- Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection.- Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning.- A new Approach to Orthopedic Surgery Planning using Deep Reinforcement Learning and Simulation.- Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations.- Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery.- Improving hexahedral-FEM-based plasticity in surgery simulation.- Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN.- Surgical Skill and Work Flow Analysis.- Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer.- OperA: Attention-Regularized Transformers for Surgical Phase Recognition.- Surgical Workflow Anticipation using Instrument Interaction.- Multi-View Surgical Video Action Detection via Mixed Global View Attention.- Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator.- Surgical Visualization and Mixed, Augmented and Virtual Reality.- Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery.- Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery.- SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality fo…